A process to estimate the value of a company based on operational performance metrics

by Cassone, Deandra Tillman

Abstract (Summary)
This research shows that industry and company related performance indicators enhance the business valuation process by providing a broader, more encompassing view of overall corporate health and a better understanding of improvement opportunity areas within a company. To incorporate performance indicators in the business valuation process, new methodologies are required to integrate the non-financial and soft data with the typical financial information used in business valuation. This requires a “re-think” of the standard business valuation process and the exploration and application of other methods and analytical techniques.

The results of this research are the definition of a problem type and the development of a new business valuation process. The problem structure has as inputs industry specific performance metrics grouped into three primary areas Production Processes, Products/Services and Marketability and Management, a fuzzy logic model with fuzzy and approximate relationships between performance metrics and financial information and crisp financial information as output. The framework for a fuzzy logic model was developed and is used to approximate relationships and model a non-linear environment. The resulting crisp financial information is then input and integrated into the traditional business valuation process.

The process was demonstrated with an example production company and with data from two regional airlines. A step-by-step example of the process was provided using the production company example to demonstrate how the results are generated and integrated with DCF business valuation. Heuristics to identify areas to improve company performance were described. Two regional airlines, individually and combined, were tested with actual data using the original fuzzy logic model structure and then the original fuzzy logic model structure was revised and new results generated. Tuning the model showed an improvement in the business valuation process performance. The benefits from this research include the definition of a new class of problems and a process to solve problems of this nature. The insights gained from this research can be applied in major disciplines such as accounting, business and finance, engineering and decision theory.

Bibliographical Information:


School:Kansas State University

School Location:USA - Kansas

Source Type:Master's Thesis

Keywords:business valuation performance metrics fuzzy logic multiple attribute decision making operational corporate value engineering industrial 0546 administration management 0454


Date of Publication:01/01/2005

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